Instructions to use usakha/Pegasus_MedPaper_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usakha/Pegasus_MedPaper_model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="usakha/Pegasus_MedPaper_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("usakha/Pegasus_MedPaper_model") model = AutoModelForSeq2SeqLM.from_pretrained("usakha/Pegasus_MedPaper_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0d4a2dd0e4d6d84aacf32e5e1692708a054895eb8dc3a3947b21661c0b60a94
- Size of remote file:
- 2.28 GB
- SHA256:
- 112fc4bc671bce2f59f53c76a67f03c41b00425a7978de7d3492c447ed137943
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